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//
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <OpaqueDelegateUtils.hpp>
namespace armnnOpaqueDelegate
{
TfLiteStatus VisitStridedSliceOperator(DelegateData& delegateData,
TfLiteOpaqueContext* tfLiteContext,
TfLiteOpaqueNode* tfLiteNode,
int nodeIndex,
int32_t tfLiteStridedSliceOperatorCode)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
// Read inputs [input, begin, end, strides]
// Gather input indices and use to get input tensor.
const int* inputTensors;
int numInputs;
if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
std::vector<const TfLiteOpaqueTensor*> tfLiteInputTensors;
tfLiteInputTensors.reserve(numInputs);
for (int i = 0; i < numInputs; i++)
{
const TfLiteOpaqueTensor* inputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[i]);
tfLiteInputTensors.push_back(inputTensor);
if (!IsValid(tfLiteContext, inputTensor, tfLiteStridedSliceOperatorCode, nodeIndex))
{
return kTfLiteError;
}
}
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensors[0]);
// We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs
unsigned int inputRank = inputTensorInfo.GetNumDimensions();
auto ReadInt32Input = [&](int inputIndex, std::vector<int32_t>& outputData) -> TfLiteStatus
{
if (TfLiteOpaqueTensorType(tfLiteInputTensors[inputIndex]) != kTfLiteInt32)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLitearmnnOpaqueDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need"
" to be of type int32. Operator: #%d node #%d: ",
tfLiteStridedSliceOperatorCode, nodeIndex);
return kTfLiteError;
}
uint32_t rank = TfLiteOpaqueTensorNumDims(tfLiteInputTensors[inputIndex]);
if (rank != 1)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLitearmnnOpaqueDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need"
" to be a 1D-Tensor. Operator: #%d node #%d: ",
tfLiteStridedSliceOperatorCode, nodeIndex);
return kTfLiteError;
}
uint32_t numValues = TfLiteOpaqueTensorDim(tfLiteInputTensors[inputIndex], 0);
if (numValues != inputRank)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLitearmnnOpaqueDelegate: The number of values in the Begin-, End- and Stride-Tensors of the "
"StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ",
tfLiteStridedSliceOperatorCode, nodeIndex);
return kTfLiteError;
}
// return tensor data
auto* tensorDataPtr = static_cast<uint32_t*>(TfLiteOpaqueTensorData(tfLiteInputTensors[inputIndex]));
outputData.assign(tensorDataPtr, tensorDataPtr + numValues);
return kTfLiteOk;
};
std::vector<int32_t> beginData;
if (ReadInt32Input(1, beginData) != kTfLiteOk)
return kTfLiteError;
std::vector<int32_t> endData;
if (ReadInt32Input(2, endData) != kTfLiteOk)
return kTfLiteError;
std::vector<int32_t> strideData;
if (ReadInt32Input(3, strideData) != kTfLiteOk)
return kTfLiteError;
// parse built in options
auto* nodeParameters = reinterpret_cast<TfLiteStridedSliceParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
// Write all data to the descriptor
armnn::StridedSliceDescriptor descriptor;
descriptor.m_Begin = std::move(beginData);
descriptor.m_End = std::move(endData);
descriptor.m_Stride = std::move(strideData);
descriptor.m_BeginMask = nodeParameters->begin_mask;
descriptor.m_EllipsisMask = nodeParameters->ellipsis_mask;
descriptor.m_EndMask = nodeParameters->end_mask;
descriptor.m_NewAxisMask = nodeParameters->new_axis_mask;
descriptor.m_ShrinkAxisMask = nodeParameters->shrink_axis_mask;
descriptor.m_DataLayout = armnn::DataLayout::NHWC;
// Validate output
// Gather output indices and use to get output tensor.
const int* outputTensors;
int numOutputs;
if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteStridedSliceOperatorCode, nodeIndex))
{
return kTfLiteError;
}
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor);
bool isSupported = false;
armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
{
FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("STRIDED_SLICE",
tfLiteContext,
IsStridedSliceSupported,
delegateData.m_Backends,
isSupported,
setBackend,
inputTensorInfo,
outInfo,
descriptor);
};
if (!delegateData.m_Network)
{
validateFunc(outputTensorInfo, isSupported);
return isSupported ? kTfLiteOk : kTfLiteError;
}
// Add a StridedSlice layer
auto layerName = GetName(armnn::LayerType::StridedSlice, nodeIndex);
armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor, layerName.c_str());
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
// try to connect the Constant Inputs if there are any
if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode, nodeIndex) != kTfLiteOk)
{
return kTfLiteError;
}
// Connect
return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
}
} // namespace armnnOpaqueDelegate
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